Navigation Ability Research Articles

Cognitive Maps for a Non-Euclidean Environment: Path Integration and Spatial Memory on a Sphere.

Humans build mental models of the world and utilize them for various cognitive tasks. The exact form of cognitive maps is not fully understood, especially for novel and complex environments beyond the flat Euclidean environment. To address this gap, we investigated path integration-a critical process underlying cognitive mapping-and spatial-memory capacity on the spherical (non-Euclidean) and planar (Euclidean) environments in young healthy adults (N = 20) using immersive virtual reality. We observed a strong Euclidean bias during the path-integration task on the spherical surface, even among participants who possessed knowledge of non-Euclidean geometry. Notably, despite this bias, participants demonstrated reasonable navigation ability on the sphere. This observation and simulation suggest that humans navigate nonflat surfaces by constructing locally confined Euclidean maps and flexibly combining them. This insight sheds light on potential neural mechanisms and behavioral strategies for solving complex cognitive tasks.

Aerial electroreception

Electroreception is the capacity of living organisms to detect the presence of electricity, usually studied in the aquatic environment. Electroreception in air, however, has received much less attention until relatively recently. Understanding how and why aerial electroreception may work requires a multidisciplinary framework, anchored in both the physics of static electricity and the ecology of sensory biology. In essence, the novel challenge arises from the fact that air is a much less conductive medium than water. Yet, recent research on terrestrial arthropods, including bees, flies, spiders, worms and caterpillars, has unveiled sensitivity to electric fields in different sensory ecological contexts. For each aerial organism considered thus far, filiform hairs and/or the antennae have been proposed to be the specialised sensory structures enabling detection based on both empirical and theoretical evidence. This newfound sensory modality reveals a previously unrecognised source of information, a new informational ecological niche integral to diverse life histories and navigational abilities, which remarkably involves animals, plants and atmospheric electricity (Figure 1). Understanding aerial electroreception in arthropods opens avenues for exploring their behaviour and ecology in diverse environments and sheds light on the evolution of sensory adaptations in terrestrial organisms. Because, as is known today, humans are not sensitive to weak electric fields, challenges arise in our comprehension of the elusive and discrete nature of aerial electric fields, and how they could be detected and used by terrestrial organisms.

Transcriptomic Signature of Spatial Navigation in Brains ofDesert Ants.

Navigation is crucial for central-place foragers to locate food and return to the nest. Cataglyphis ants are renowned for their advanced navigation abilities, relying on landmark cues and path integration. This study aims to uncover the transcriptomic basis of exceptional spatial learning in the central nervous system of Cataglyphis niger. Ants navigated a maze with a food reward, and we examined expression changes linked to correct decisions in subsequent runs. Correct decisions correlated with expression changes in the optic lobes, but not the central brain, showing a downregulation of genes associated with sucrose response and Creb3l1. The latter gene is homologous to Drosophila crebA, which is essential for long-term memory formation. To understand how ants use distance information during path integration, we analyzed expression shifts associated with the last distance traveled. We uncovered a transcriptomic footprint in the central brain, but not in the optic lobes, with genes enriched for energy consumption and neurological functions, including neuronal projection development, synaptic target inhibition, and recognition processes. This suggests that transcriptional activity in the central brain is necessary for estimating distance traveled, which is crucial for path integration. Our study supports the distinct roles of different brain parts for navigation in Cataglyphis ants.

Intelligent mobile robot navigation in unknown and complex environment using reinforcement learning technique

The usage of mobile robots (MRs) has expanded dramatically in the last several years across a wide range of industries, including manufacturing, surveillance, healthcare, and warehouse automation. To ensure the efficient and safe operation of these MRs, it is crucial to design effective control strategies that can adapt to changing environments. In this paper, we propose a new technique for controlling MRs using reinforcement learning (RL). Our approach involves mathematical model generation and later training a neural network (NN) to learn a policy for robot control using RL. The policy is learned through trial and error, where MR explores the environment and receives rewards based on its actions. The rewards are designed to encourage the robot to move towards its goal while avoiding obstacles. In this work, a deep Q-learning (QL) agent is used to enable robots to autonomously learn to avoid collisions with obstacles and enhance navigation abilities in an unknown environment. When operating MR independently within an unfamiliar area, a RL model is used to identify the targeted location, and the Deep Q-Network (DQN) is used to navigate to the goal location. We evaluate our approach using a simulation using the Epsilon-Greedy algorithm. The results show that our approach outperforms traditional MR control strategies in terms of both efficiency and safety.

The Detection of Lymph Node Metastasis Metastases Using a Near-Infrared Fluorescent Probe Based on Tumor-Targeted Monoclonal Antibody Antibodies Specific: A Prospective Study in a Nude Mouse Model

Background: To identify the metastatic lymph nodes and remove them accurately, the fluorescent surgical navigation ability of the ovarian cancer-specific fluorescent probe COC183B2-800 was assessed to verify the metastatic lymph nodes in the nude mouse model. Methods: The nude mouse model related to lymph node metastases in human ovarian cancer was established using the SKOV3-ip1 cell line. Besides, the COC183B2-800 probe (IRDye800CW Ester conjugated COC183B2 antibody) was fabricated. Moreover, in vivo fluorescence imaging was performed to determine the ability of the COC183B2-800 fluorescent probe to identify metastatic lymph nodes in the nude mouse model. Results: The nude mouse model related to lymph node metastases in human ovarian cancer was successfully established. In vivo fluorescence imaging was performed 30 hours after the injection of the COC183B2-800 fluorescent probe (25 μg) into the animal model, which can achieve specific imaging of metastatic lymph nodes. All metastatic lymph nodes were detected in vivo and in vitro (8/8), and only 1 negative lymph node with reactive enlargement showed a false positive fluorescent signal. Conclusions: The targeted fluorescent probe COC183B2-800 can be employed to identify metastatic lymph nodes in the nude mouse model related to lymph node metastases in human ovarian cancer with high specificity and sensitivity. Targeted fluorescence imaging using COC183B2-800 is expected to become a method to achieve precise lymphadenectomy.

Minimal perception: enabling autonomy in resource-constrained robots.

The rapidly increasing capabilities of autonomous mobile robots promise to make them ubiquitous in the coming decade. These robots will continue to enhance efficiency and safety in novel applications such as disaster management, environmental monitoring, bridge inspection, and agricultural inspection. To operate autonomously without constant human intervention, even in remote or hazardous areas, robots must sense, process, and interpret environmental data using only onboard sensing and computation. This capability is made possible by advancements in perception algorithms, allowing these robots to rely primarily on their perception capabilities for navigation tasks. However, tiny robot autonomy is hindered mainly by sensors, memory, and computing due to size, area, weight, and power constraints. The bottleneck in these robots lies in the real-time perception in resource-constrained robots. To enable autonomy in robots of sizes that are less than 100 mm in body length, we draw inspiration from tiny organisms such as insects and hummingbirds, known for their sophisticated perception, navigation, and survival abilities despite their minimal sensor and neural system. This work aims to provide insights into designing a compact and efficient minimal perception framework for tiny autonomous robots from higher cognitive to lower sensor levels.

Excessive noise explains the impaired visually-guided navigation abilities in adults with Williams syndrome: a computational approach

Excessive noise explains the impaired visually-guided navigation abilities in adults with Williams syndrome: a computational approach

Lessons in cognition: A review of maze designs and procedures used to measure spatial learning in fish.

The use of different mazes to assess spatial learning has become more common in fish behavior studies in recent decades. This increase in fish cognition research has opened the door to numerous possibilities for exciting and diverse questions, such as identifying ecological drivers of spatial cognition and understanding the role individual variation plays in navigational abilities. There are many different types of mazes, each with its own specific considerations, making it challenging to determine exactly which spatial test is the most relevant and appropriate for a particular experiment. Many spatial mazes, such as the T-maze and Y-maze, have been successfully adapted from rodent studies, particularly with respect to zebrafish, a widely accepted non-mammalian model in biomedical studies. Standardization across studies is increasing with these easily accessible maze designs, validating them for use in fish; however, variations in design (e.g., length of arms and scale) and procedure still exist, and the impact of these variations on results is largely unknown. The efforts to standardize mazes outside zebrafish work are also more limited. Other mazes have been developed specifically for use on fish, with design modifications varying widely, making it difficult to draw comparisons. In this review, we have highlighted the many design and procedural elements that should be considered for the acquisition of reliable behavioral data, with the goal of drawing readers' attention to aspects of experimentation that are often not given the careful consideration that they deserve. We then argue that additional focused research and reporting is needed to produce more reliable methods in spatial learning research across a broader range of subjects.

Evolutionary Optimization for Unmanned Underwater Vehicle Navigation

Unmanned Underwater Vehicles (UUVs) play a vital role in various underwater exploration and surveillance tasks. However, the effective navigation of UUVs in complex underwater environments poses significant challenges due to factors such as limited communication, dynamic currents, and other difficulties. Evolutionary optimization techniques have developed as promising tools for enhancing UUV navigation abilities. This review provides a brief overview of the application of evolutionary optimization algorithms, including genetic algorithms, evolutionary approaches, and particle swarm optimization, in the context of UUV navigation. The fundamental principles of these algorithms and their applications in path planning, path optimization, localization, obstacle avoidance, and mission planning for UUVs are discussed in brief. Through an analysis of existing literature and case studies, the use of evolutionary optimization in improving the navigation efficiency, accuracy, and robustness of UUVs is highlighted. Additionally, current challenges were identified, and future research directions to advance the integration of evolutionary optimization techniques in UUV navigation systems are also discussed. Overall, this aims to provide insights into the potential of evolutionary optimization for addressing the navigation challenges faced by unmanned underwater vehicles and promoting advancements in underwater exploration and surveillance technologies.

Accuracy, rationality and specialization in a generalized model of collective navigation.

Animal navigation is a key behavioural process, from localized foraging to global migration. Within groups, individuals may improve their navigational accuracy by following those with more experience or knowledge, by pooling information from many directional estimates ('many wrongs') or some combination of these strategies. Previous agent-based simulations have highlighted that homogeneous leaderless groups can improve their collective navigation accuracy when individuals preferentially copy the movement directions of their neighbours while giving a low weighting to their own navigational knowledge. Meanwhile, other studies have demonstrated how specialized leaders may emerge, and that a small number of such individuals can improve group-level navigation performance. However, in general, these earlier results either lack a full mathematical grounding or do not fully consider the effect of individual self-interest. Here we derive and analyse a mathematically tractable model of collective navigation. We demonstrate that collective navigation is compromised when individuals seek to optimize their own accuracy in both homogeneous groups and those with differing navigational abilities. We further demonstrate how heterogeneous navigational strategies (specialized leaders and followers) may evolve within the model. Our results thus unify different lines of research in collective navigation and highlight the importance of individual selection in determining group composition and performance.

Three-dimensional positioning and trajectory tracking of pigeons in large indoor spaces

Animal localization and trajectory tracking are of great value for the study of brain spatial cognition and navigation neural mechanisms. However, traditional optical lens video positioning techniques are limited in their scope due to factors such as camera perspective. For pigeons with excellent spatial cognition and navigation abilities, based on the beacon positioning technology, a three-dimensional (3D) trajectory positioning and tracking method suitable for large indoor spaces was proposed, and the corresponding positioning principle and hardware structure were provided. The results of in vitro and in vivo experiments showed that the system could achieve centimeter-level positioning and trajectory tracking of pigeons in a space of 360 cm × 200 cm × 245 cm. Compared with traditional optical lens video positioning techniques, this system has the advantages of large space, high precision, and high response speed. It not only helps to study the neural mechanisms of pigeon 3D spatial cognition and navigation, but also has high reference value for trajectory tracking of other animals.

How spatial-cue reliability affects navigational performance in young and older adults

ABSTRACT Navigational abilities decline with age, but the cognitive underpinnings of this cognitive decline remain partially understood. Navigation is guided by landmarks and self-motion cues, that we address when estimating our location. These sources of spatial information are often associated with noise and uncertainty, thus posing a challenge during navigation. To overcome this challenge, humans and other species rely on navigational cues according to their reliability: reliable cues are highly weighted and therefore strongly influence our spatial behavior, compared to less reliable ones. We hypothesize that older adults do not efficiently weigh spatial cues, and accordingly, the reliability levels of navigational cues may not modulate their spatial behavior, as with younger adults. To test this, younger and older adults performed a virtual navigational task, subject to modified reliability of landmarks and self-motion cues. The findings revealed that while increased reliability of spatial cues improved navigational performance across both age groups, older adults exhibited diminished sensitivity to changes in landmark reliability. The findings demonstrate a cognitive mechanism that could lead to impaired navigation abilities in older adults.

Space optical communication system for space optical networks and deep space exploration

The acquisition time of tens to hundreds of seconds in the optical link between satellites makes it difficult to meet the needs of constructing spatial optical networks. In addition, as a basic requirement for deep space explorers, autonomous attitude determination and autonomous navigation demand the installation of separate, expensive, and complex inertial devices, and the communication data rate is too low to meet the timely transmission of large amounts of data. In this paper, we proposed and developed a multifunctional fusion space optical communication system for space optical networks and deep space exploration, which has the functions of autonomous attitude determination, autonomous navigation, and high-speed optical communication. The sub-second acquisition time can meet the requirements of space optical network construction, and the ability of autonomous attitude determination and autonomous navigation significantly reduce the amount of R&D expenses of the explorer; decrease the volume, weight, and power consumption of the explorer; and improve the reliability and autonomous survival ability of the explorer. The paper provides the structure, working principle, and main algorithm models and conducts a feasibility analysis and field experiments. The experimental results showed that the average open-loop pointing accuracy of the optical terminal is 95.8 µrad (attitude determination accuracy), which can be improved to 39.1 µrad after filtering, and the acquisition time is less than 1 s. For deep space exploration, the navigation accuracy is less than 67.6 km in the cruise phase and 10 km in the acquisition phase, and field experiments have also proven its feasibility. The significance of our research work lies in proposing what we believe to be a new system operation scheme and design method for optical communication systems, and its results can be widely applied in all fields of space optical communication.

Embodied Spatial Navigation Training in Mild Cognitive Impairment: A Proof-of-Concept Trial.

Egocentric and allocentric spatial memory impairments affect the navigation abilities of older adults with mild cognitive impairment (MCI). Embodied cognition research hints that specific aids can be implemented into virtual reality (VR) training to enhance spatial memory. In this study, we preliminarily tested 'ANTaging', an embodied-based immersive VR training for egocentric and allocentric memory, compared to treatment as usual (TAU) spatial training in MCI. MCI patients were recruited for this controlled trial. A cognitive battery was administered at pre-test, after ten sessions of ANTaging or TAU intervention, and at 3-month follow-up (FU). The primary outcomes were spatial cognition tests (Corsi supra-span, CSS; Manikin test, MT). VR egocentric and allocentric performance was also collected. We found that ANTaging significantly improved MT scores at FU compared to TAU. CSS slightly improved in both groups. Concerning secondary outcomes, auditory-verbal forgetting significantly improved at post-test in the ANTaging but not TAU group and significantly declined at FU in the TAU but not in the ANTaging group. Global cognition significantly improved at FU for TAU and remained stable for ANTaging. Other tests showed no improvement or deterioration. Clinical significance showed that ANTaging is effective for CSS. Virtual egocentric and allocentric memory performance improved across ANTaging sessions. ANTaging holds the potential to be superior for improving spatial cognition in MCI compared to TAU. Embodied cognition research provides insights for designing effective spatial navigation rehabilitation in aging.

Study on a model analysis method of water flow characteristics in channel entrance area

With the development of inland waterway transport in our country, the demand for inland waterway navigation is increasing day by day, and the navigation safety requirements of ships are also increasing day by day. The flow condition is very important for the safe running of the ship, it not only determines the safety of the ship entering and leaving the lock, but also determines the key factor of the navigation ability of the hub. Based on the mathematical model, this paper studies the navigable flow conditions in the entrance area of the curved branching river through the modeling technology of the curved branching river, explores the peer flow characteristics of the curved branching river, and puts forward an effective measure to improve the navigable flow conditions in the entrance area of the curved river, which is of great practical significance and engineering value.

Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks

Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. However, biases introduced by the apparatus, environment, or experimentalist represent a critical challenge to the test validity. We have recently developed the Modified Barnes Maze (MBM) task, a spatial learning paradigm that overcomes inherent behavioral biases of animals in the classical Barnes maze. The specific combination of spatial strategies employed by mice is often considered representative of the level of cognitive resources used. Herein, we have developed a convolutional neural network-based classifier of exploration strategies in the MBM that can effectively provide researchers with enhanced insights into cognitive traits in mice. Following validation, we compared the learning performance of female and male C57BL/6J mice, as well as that of Ts65Dn mice, a model of Down syndrome, and 5xFAD mice, a model of Alzheimer’s disease. Male mice exhibited more effective navigation abilities than female mice, reflected in higher utilization of effective spatial search strategies. Compared to wildtype controls, Ts65Dn mice exhibited delayed usage of spatial strategies despite similar success rates in completing this spatial task. 5xFAD mice showed increased usage of non-spatial strategies such as Circling that corresponded to higher latency to reach the target and lower success rate. These data exemplify the need for deeper strategy classification tools in dissecting complex cognitive traits. In sum, we provide a machine-learning-based strategy classifier that extends our understanding of mice’s spatial learning capabilities while enabling a more accurate cognitive assessment.

Neural and sensory basis of homing behavior in the invasive cane toad, Rhinella marina.

The behavioral, sensory, and neural bases of vertebrate navigation are primarily described in mammals and birds. However, we know much less about navigational abilities and mechanisms of vertebrates that move on smaller scales, such as amphibians. To address this knowledge gap, we conducted an extensive field study on navigation in the cane toad, Rhinella marina. First, we performed a translocation experiment to describe how invasive toads in Hawai'i navigate home following displacements of up to one kilometer. Next, we tested the effect of olfactory and magnetosensory manipulations on homing, as these senses are most commonly associated with amphibian navigation. We found that neither ablation alone prevents homing, suggesting that toad navigation is multimodal. Finally, we tested the hypothesis that the medial pallium, the amphibian homolog to the hippocampus, is involved in homing. By comparing neural activity across homing and non-homing toads, we found evidence supporting the involvement of the medial pallium, lateral pallium, and septum in navigation, suggesting a conservation of neural structures supporting navigation across vertebrates. Our study lays the foundation to understand the behavioral, sensory, and neural bases of navigation in amphibians and to further characterize the evolution of behavior and neural structures in vertebrates.

Light-driven rGO/Cu2 + 1O tubular nanomotor with active targeted drug delivery for combination treatment of cancer cells.

The unprecedented navigation ability in micro/nanoscale and tailored functionality tunes micro/nanomotors as new target drug delivery systems, openup new horizons for biomedical applications. Herein, we designed a light-driven rGO/Cu2 + 1O tubular nanomotor for active targeting of cancer cells as a drug delivery system. The propulsion performance is greatly enhanced in real cell media (5% glucose cells isotonic solution), attributing to the introduction of oxygen vacancy and reduced graphene oxide (rGO) layer for separating photo-induced electron-hole pairs. The motion speed and direction can be readily modulated. Meanwhile, doxorubicin (DOX) can be loaded quickly on the rGO layer because of π-π bonding effect. The Cu2 + 1O matrix in the tiny robots not only serves as a photocatalyst to generate achemical concentration gradient asthe driving force but also acts as ananomedicine to kill cancer cells as well. The strong propulsion of light-driven rGO/Cu2 + 1O nanomotors coupled with tiny size endow them with active transmembrane transport, assisting DOX and Cu2 + 1O breaking through the barrier of thecell membrane. Compared with non-powered nanocarrier and free DOX, light-propelled rGO/Cu2 + 1O nanomotors exhibit greater transmembrane transport efficiency and significant therapeutic efficacy. This proof-of-concept nanomotor design presents an innovative approach against tumor, enlarging the list of biomedical applications of light-driven micro/nanomotors to the superficial tissue treatment.

Behavioral Disorders of Spatial Cognition in Patients with Mild Cognitive Impairment Due to Alzheimer's Disease (The BDSC-MCI Project): Ecological Validity of the Corsi Learning Suvra-Span Test.

Spatial navigation deficits are reported as early symptoms of Alzheimer's disease (AD) alongside episodic memory ones. The aim of the present study was to ascertain whether neuropsychological deficits of visuospatial long-term memory can predict behavioral alterations during the navigation of older adults in novel urban environments along the normal aging-dementia continuum of the Alzheimer's type. A total of 24 community-dwelling patients with Mild Cognitive Impairment (MCI) due to AD, 27 individuals with subjective cognitive decline (SCD), and 21 healthy controls were assessed in terms of their sequential egocentric and allocentric navigation abilities by using a modified version of the Detour Navigation Test, and neuropsychologically tested by the Corsi learning suvra-span (CLSS) test. Generalized linear models were adopted to verify whether the scores obtained by the three groups in the CLSS test predicted wrong turns and moments of hesitation during the navigation task, with the results presented as topographical disorientation scores. Higher scores in the CLSS test predicted fewer wrong turns (b = -0.05; z = -2.91; p = 0.004; net of between-groups differences) and moments of hesitation for patients with MCI due to AD (b = -0.14; z = -2.43; p = 0.015), and individuals with SCD (b = -0.17; z = -3.85; p < 0.001). Since the CLSS test has been reported to be a reliable measure of ecological navigational abilities in the progression towards AD dementia, we recommend its use in clinical practice and highlight implications for future research.

Black Titania Janus Mesoporous Nanomotor for Enhanced Tumor Penetration and Near-Infrared Light-Triggered Photodynamic Therapy.

Thanks to their excellent photoelectric characteristics to generate cytotoxic reactive oxygen species (ROS) under the light-activation process, TiO2 nanomaterials have shown significant potential in photodynamic therapy (PDT) for solid tumors. Nevertheless, the limited penetration depth of TiO2-based photosensitizers and excitation sources (UV/visible light) for PDT remains a formidable challenge when confronted with complex tumor microenvironments (TMEs). Here, we present a H2O2-driven black TiO2 mesoporous nanomotor with near-infrared (NIR) light absorption capability and autonomous navigation ability, which effectively enhances solid tumor penetration in NIR light-triggered PDT. The nanomotor was rationally designed and fabricated based on the Janus mesoporous nanostructure, which consists of a NIR light-responsive black TiO2 nanosphere and an enzyme-modified periodic mesoporous organosilica (PMO) nanorod that wraps around the TiO2 nanosphere. The overexpressed H2O2 can drive the nanomotor in the TME under catalysis of catalase in the PMO domain. By precisely controlling the ratio of TiO2 and PMO compartments in the Janus nanostructure, TiO2&PMO nanomotors can achieve optimal self-propulsive directionality and velocity, enhancing cellular uptake and facilitating deep tumor penetration. Additionally, by the decomposition of endogenous H2O2 within solid tumors, these nanomotors can continuously supply oxygen to enable highly efficient ROS production under the NIR photocatalysis of black TiO2, leading to intensified PDT effects and effective tumor inhibition.